Progressive image transmission based on image spatio-temporal decomposition by sigma-delta cellular neural network
Hisashi Aomori, Ryohei Mizutani, Hideharu Toda, Tsuyoshi Otake · Nonlinear Theory and Its Applications IEICE · 2022
In this paper, we propose a novel progressive image transmission framework based on spatio-temporal image decomposition and synthesis by the SD-CNN. In our method, we redesign the baseline SD-CNN and the weighted sum is introduced in the accumulator. This innovation enables lossless or near-lossless progressive image transmission. Experimental results in various test images support that the image reconstruction performance of the SD-CNN has dramatically improved by our method.